ISAR Imaging using A Greedy Kalman Filtering Method with Sparse Constraints
Konferenz: EUSAR 2016 - 11th European Conference on Synthetic Aperture Radar
06.06.2016 - 09.06.2016 in Hamburg, Germany
Tagungsband: EUSAR 2016
Seiten: 5Sprache: EnglischTyp: PDF
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Autoren:
Wang, Ling (Key Lab. of Radar Imaging and Microwave Photonics of the Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China & Center for Sensor Systems, University of Siegen, Siegen 57076, Germany)
Loffeld, Otmar (Center for Sensor Systems, University of Siegen, Siegen 57076, Germany)
Qian, Yulei (Key Lab. of Radar Imaging and Microwave Photonics of the Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)
Inhalt:
We presented a greedy kalman filtering based imaging method for ISAR with sparse constraints. As the kalman filter has excellent estimation performance in statistical settings for linear problems, the presented method leads to good image reconstruction results for real ISAR data. We also exploits the sparsity of the scene in the wavelet domain to improve the reconstruction of region-like features of the ISAR targets except for the point-like features. The images obtained by exploiting the sparsity in different domains are synthesized leading to better reconstructions.